1. This is an extension of theogic behind Cohen's d (doesn't make it good).
2. This is also the parameterization in the popular BayesFactor package (and by extention JASP/jamovi) which has been criticized:
link.springer.com/article/10.1...
2. This is also the parameterization in the popular BayesFactor package (and by extention JASP/jamovi) which has been criticized:
link.springer.com/article/10.1...
October 6, 2025 at 6:25 PM
1. This is an extension of theogic behind Cohen's d (doesn't make it good).
2. This is also the parameterization in the popular BayesFactor package (and by extention JASP/jamovi) which has been criticized:
link.springer.com/article/10.1...
2. This is also the parameterization in the popular BayesFactor package (and by extention JASP/jamovi) which has been criticized:
link.springer.com/article/10.1...
Calculation of max(BF01) for the default JZS t-test requires numerical integeration (no closed form), but you can conveniently calculate it using {BayesFactor}, e.g.:
> as.vector(1/BayesFactor::meta.ttestBF(t = 0, n1 = 100, rscale=sqrt(2)/2))
Null, d=0
9.033045
> as.vector(1/BayesFactor::meta.ttestBF(t = 0, n1 = 100, rscale=sqrt(2)/2))
Null, d=0
9.033045
August 20, 2026 at 8:36 AM
Calculation of max(BF01) for the default JZS t-test requires numerical integeration (no closed form), but you can conveniently calculate it using {BayesFactor}, e.g.:
> as.vector(1/BayesFactor::meta.ttestBF(t = 0, n1 = 100, rscale=sqrt(2)/2))
Null, d=0
9.033045
> as.vector(1/BayesFactor::meta.ttestBF(t = 0, n1 = 100, rscale=sqrt(2)/2))
Null, d=0
9.033045
#statstab #414 The Bayes factor {shiny app}
Thoughts: It's almost the start of term, so here is another teaching tool for learning about Bayes Factors.
#nhbt #bayes #bayesfactor #learing #pedagogy #shiny #r
statsedge.org/shiny/LearnBF/
Thoughts: It's almost the start of term, so here is another teaching tool for learning about Bayes Factors.
#nhbt #bayes #bayesfactor #learing #pedagogy #shiny #r
statsedge.org/shiny/LearnBF/
The Bayes factor
statsedge.org
September 4, 2025 at 4:36 PM
#statstab #414 The Bayes factor {shiny app}
Thoughts: It's almost the start of term, so here is another teaching tool for learning about Bayes Factors.
#nhbt #bayes #bayesfactor #learing #pedagogy #shiny #r
statsedge.org/shiny/LearnBF/
Thoughts: It's almost the start of term, so here is another teaching tool for learning about Bayes Factors.
#nhbt #bayes #bayesfactor #learing #pedagogy #shiny #r
statsedge.org/shiny/LearnBF/
#statstab #538 A Tutorial on Conducting and Interpreting a Bayesian Independent T-Test Using Open-Source Software
Thoughts: OK as a beginner guide, but not more.
#bayesian #bayesfactor #priors #jasp #ttest #tutorial #guide
onlinelibrary.wiley.com/doi/epdf/10....
Thoughts: OK as a beginner guide, but not more.
#bayesian #bayesfactor #priors #jasp #ttest #tutorial #guide
onlinelibrary.wiley.com/doi/epdf/10....
A Tutorial on Conducting and Interpreting a Bayesian Independent T‐Test Using Open‐Source Software
onlinelibrary.wiley.com
May 26, 2026 at 7:39 PM
#statstab #538 A Tutorial on Conducting and Interpreting a Bayesian Independent T-Test Using Open-Source Software
Thoughts: OK as a beginner guide, but not more.
#bayesian #bayesfactor #priors #jasp #ttest #tutorial #guide
onlinelibrary.wiley.com/doi/epdf/10....
Thoughts: OK as a beginner guide, but not more.
#bayesian #bayesfactor #priors #jasp #ttest #tutorial #guide
onlinelibrary.wiley.com/doi/epdf/10....
#statstab #360 Bayes Factor Design Analysis {bfda}
Thoughts: Sample size planning is confusing at first with Bayesian. But BFDA is the quick answer.
#bfda #bayesian #bayesfactor #samplesize #power #errorrate
shinyapps.org/apps/BFDA/
Thoughts: Sample size planning is confusing at first with Bayesian. But BFDA is the quick answer.
#bfda #bayesian #bayesfactor #samplesize #power #errorrate
shinyapps.org/apps/BFDA/
Experience Statistics
shinyapps.org
June 6, 2025 at 7:01 PM
#statstab #360 Bayes Factor Design Analysis {bfda}
Thoughts: Sample size planning is confusing at first with Bayesian. But BFDA is the quick answer.
#bfda #bayesian #bayesfactor #samplesize #power #errorrate
shinyapps.org/apps/BFDA/
Thoughts: Sample size planning is confusing at first with Bayesian. But BFDA is the quick answer.
#bfda #bayesian #bayesfactor #samplesize #power #errorrate
shinyapps.org/apps/BFDA/
#statstab #453 {Bayes Power}
A General Application of Power and Sample Size Calculation for the Bayes Factors
Thoughts: Blending frequentist notions of power with bayes hypothesis testing.
#poweranalysis #bayesian #bayesfactor #errorrate #rstats #nhbt
doi.org/10.31234/osf...
A General Application of Power and Sample Size Calculation for the Bayes Factors
Thoughts: Blending frequentist notions of power with bayes hypothesis testing.
#poweranalysis #bayesian #bayesfactor #errorrate #rstats #nhbt
doi.org/10.31234/osf...
OSF
doi.org
November 5, 2025 at 7:08 PM
#statstab #453 {Bayes Power}
A General Application of Power and Sample Size Calculation for the Bayes Factors
Thoughts: Blending frequentist notions of power with bayes hypothesis testing.
#poweranalysis #bayesian #bayesfactor #errorrate #rstats #nhbt
doi.org/10.31234/osf...
A General Application of Power and Sample Size Calculation for the Bayes Factors
Thoughts: Blending frequentist notions of power with bayes hypothesis testing.
#poweranalysis #bayesian #bayesfactor #errorrate #rstats #nhbt
doi.org/10.31234/osf...
#statstab #514 A puzzle of proportions
Thoughts: "Two popular Bayesian tests can yield dramatically different conclusions"
Model specification is important.
#bayesian #bayes #bayesfactor #nulleffects #proportions
doi.org/10.1002/sim....
Thoughts: "Two popular Bayesian tests can yield dramatically different conclusions"
Model specification is important.
#bayesian #bayes #bayesfactor #nulleffects #proportions
doi.org/10.1002/sim....
A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions
Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains, it is crucial to be able to quantify evidence for the absence of ...
doi.org
March 26, 2026 at 6:29 PM
#statstab #514 A puzzle of proportions
Thoughts: "Two popular Bayesian tests can yield dramatically different conclusions"
Model specification is important.
#bayesian #bayes #bayesfactor #nulleffects #proportions
doi.org/10.1002/sim....
Thoughts: "Two popular Bayesian tests can yield dramatically different conclusions"
Model specification is important.
#bayesian #bayes #bayesfactor #nulleffects #proportions
doi.org/10.1002/sim....
#statstab #346 Jeffreys-Lindley paradox
Thoughts: I like this short explanation of the "paradox" of why frequentist and bayesian inference can differ.
#paradox #frequentist #bayesian #inference #bayesfactor #pvalue #explanation
michael-franke.github.io/intro-data-a...
Thoughts: I like this short explanation of the "paradox" of why frequentist and bayesian inference can differ.
#paradox #frequentist #bayesian #inference #bayesfactor #pvalue #explanation
michael-franke.github.io/intro-data-a...
17.10 Jeffreys-Lindley paradox | An Introduction to Data Analysis
Introductory text for statistics and data analysis (using R)
michael-franke.github.io
May 19, 2025 at 1:50 PM
#statstab #346 Jeffreys-Lindley paradox
Thoughts: I like this short explanation of the "paradox" of why frequentist and bayesian inference can differ.
#paradox #frequentist #bayesian #inference #bayesfactor #pvalue #explanation
michael-franke.github.io/intro-data-a...
Thoughts: I like this short explanation of the "paradox" of why frequentist and bayesian inference can differ.
#paradox #frequentist #bayesian #inference #bayesfactor #pvalue #explanation
michael-franke.github.io/intro-data-a...
#statstab #467 Hypothesis testing, model selection, model comparison some thoughts
Thoughts: An excellent (but too short) discussion on bayesian inference.
#bayesian #bayesfactor #modelselection #inference #NBHT #BF #ROPE #primer
discourse.mc-stan.org/t/hypothesis...
Thoughts: An excellent (but too short) discussion on bayesian inference.
#bayesian #bayesfactor #modelselection #inference #NBHT #BF #ROPE #primer
discourse.mc-stan.org/t/hypothesis...
Hypothesis testing, model selection, model comparison - some thoughts
EDIT: This was an attempt to write guidance. It turns out I stepped quite far from my depth and the text sounded much more conclusive than it should. I think it is correct to currently just classify i...
discourse.mc-stan.org
November 25, 2025 at 6:58 PM
#statstab #467 Hypothesis testing, model selection, model comparison some thoughts
Thoughts: An excellent (but too short) discussion on bayesian inference.
#bayesian #bayesfactor #modelselection #inference #NBHT #BF #ROPE #primer
discourse.mc-stan.org/t/hypothesis...
Thoughts: An excellent (but too short) discussion on bayesian inference.
#bayesian #bayesfactor #modelselection #inference #NBHT #BF #ROPE #primer
discourse.mc-stan.org/t/hypothesis...
We also show how to leverage posterior SBC to check computation when priors are improper and we thus cannot simulate (we take the BayesFactor package as an example). 4/
March 19, 2026 at 10:58 AM
We also show how to leverage posterior SBC to check computation when priors are improper and we thus cannot simulate (we take the BayesFactor package as an example). 4/
#statstab #402 On Bayes factors for hypothesis tests {emBayes Factor}
Thoughts: On bsky there were renewed debates about BFs. This paper provides "better" priors (mixture t centred on the ES). Also some p-value BFs
#bayesian #bayesfactor #priors #cohend
link.springer.com/article/10.3...
Thoughts: On bsky there were renewed debates about BFs. This paper provides "better" priors (mixture t centred on the ES). Also some p-value BFs
#bayesian #bayesfactor #priors #cohend
link.springer.com/article/10.3...
On Bayes factors for hypothesis tests - Psychonomic Bulletin & Review
We develop alternative families of Bayes factors for use in hypothesis tests as alternatives to the popular default Bayes factors. The alternative Bayes factors are derived for the statistical analyse...
link.springer.com
August 19, 2025 at 7:18 PM
#statstab #402 On Bayes factors for hypothesis tests {emBayes Factor}
Thoughts: On bsky there were renewed debates about BFs. This paper provides "better" priors (mixture t centred on the ES). Also some p-value BFs
#bayesian #bayesfactor #priors #cohend
link.springer.com/article/10.3...
Thoughts: On bsky there were renewed debates about BFs. This paper provides "better" priors (mixture t centred on the ES). Also some p-value BFs
#bayesian #bayesfactor #priors #cohend
link.springer.com/article/10.3...
#statstab #359 A Pragmatic Approach to Statistical Testing and Estimation (PASTE)
Thought: A (basic) guide to some alternatives to p-values: bayesian posterior intervals, Bayes Factors, and AIC.
#NHST #pvalues #TOST #BayesFactor #AIC #modelcomparison
doi.org/10.1016/j.hp...
Thought: A (basic) guide to some alternatives to p-values: bayesian posterior intervals, Bayes Factors, and AIC.
#NHST #pvalues #TOST #BayesFactor #AIC #modelcomparison
doi.org/10.1016/j.hp...
A Pragmatic Approach to Statistical Testing and Estimation (PASTE)
The p-value has dominated research in education and related fields and a statistically non-significant p-value is quite commonly interpreted as ‘confirming’ the null hypothesis (H0) of ‘equivalence’. ...
doi.org
June 5, 2025 at 5:36 PM
#statstab #359 A Pragmatic Approach to Statistical Testing and Estimation (PASTE)
Thought: A (basic) guide to some alternatives to p-values: bayesian posterior intervals, Bayes Factors, and AIC.
#NHST #pvalues #TOST #BayesFactor #AIC #modelcomparison
doi.org/10.1016/j.hp...
Thought: A (basic) guide to some alternatives to p-values: bayesian posterior intervals, Bayes Factors, and AIC.
#NHST #pvalues #TOST #BayesFactor #AIC #modelcomparison
doi.org/10.1016/j.hp...
Describing how the p-value behaves under the alternative is confusing.
Although, also to my surprise, it can be done. There are p-to-BayesFactor calibrators based on limiting distributions. But these are always worse in describing what is going on than a good test statistic. Better start there!
Although, also to my surprise, it can be done. There are p-to-BayesFactor calibrators based on limiting distributions. But these are always worse in describing what is going on than a good test statistic. Better start there!
August 5, 2026 at 8:13 AM
Describing how the p-value behaves under the alternative is confusing.
Although, also to my surprise, it can be done. There are p-to-BayesFactor calibrators based on limiting distributions. But these are always worse in describing what is going on than a good test statistic. Better start there!
Although, also to my surprise, it can be done. There are p-to-BayesFactor calibrators based on limiting distributions. But these are always worse in describing what is going on than a good test statistic. Better start there!
Yes, I recall corresponding with Jeff Rouder and EJ Wagenmakers regarding this misspecification back in 2019. Happy to see this corrected and used as the new versions of JASP 😃 (maybe someday this will also be the default in the BayesFactor R package)
December 25, 2024 at 1:12 PM
Yes, I recall corresponding with Jeff Rouder and EJ Wagenmakers regarding this misspecification back in 2019. Happy to see this corrected and used as the new versions of JASP 😃 (maybe someday this will also be the default in the BayesFactor R package)
#statstab #529 How Do I Know What My Theory Predicts?
Thoughts: I'd like to see more researchers adopt Dienes' framework and way of thinking about research.
#bayesian #bayesfactor #evidence #epistemology #research #tutorial
journals.sagepub.com/doi/10.1177/...
Thoughts: I'd like to see more researchers adopt Dienes' framework and way of thinking about research.
#bayesian #bayesfactor #evidence #epistemology #research #tutorial
journals.sagepub.com/doi/10.1177/...
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
journals.sagepub.com
May 11, 2026 at 12:12 PM
#statstab #529 How Do I Know What My Theory Predicts?
Thoughts: I'd like to see more researchers adopt Dienes' framework and way of thinking about research.
#bayesian #bayesfactor #evidence #epistemology #research #tutorial
journals.sagepub.com/doi/10.1177/...
Thoughts: I'd like to see more researchers adopt Dienes' framework and way of thinking about research.
#bayesian #bayesfactor #evidence #epistemology #research #tutorial
journals.sagepub.com/doi/10.1177/...
#statstab #486 Testing Bayesian Informative Hypotheses in Five Steps With JASP and R {bain}
Thoughts: The BAIN module let's you go beyond "effect vs no effect" by specifying contrasts (hyp) & obtaining fractional BFs.
#bain #jasp #bayesfactor #bayesian #rstats #r
share.google/cTDvBO7SQM9C...
Thoughts: The BAIN module let's you go beyond "effect vs no effect" by specifying contrasts (hyp) & obtaining fractional BFs.
#bain #jasp #bayesfactor #bayesian #rstats #r
share.google/cTDvBO7SQM9C...
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
share.google
February 16, 2026 at 5:44 PM
#statstab #486 Testing Bayesian Informative Hypotheses in Five Steps With JASP and R {bain}
Thoughts: The BAIN module let's you go beyond "effect vs no effect" by specifying contrasts (hyp) & obtaining fractional BFs.
#bain #jasp #bayesfactor #bayesian #rstats #r
share.google/cTDvBO7SQM9C...
Thoughts: The BAIN module let's you go beyond "effect vs no effect" by specifying contrasts (hyp) & obtaining fractional BFs.
#bain #jasp #bayesfactor #bayesian #rstats #r
share.google/cTDvBO7SQM9C...
#statstab #382 The JASP Guidelines for Conducting and Reporting a Bayesian Analysis
Thoughts: @jaspstats.bsky.social is often people's first attempt at Bayesian statistics. But proper inference and reporting is crucial
#JASP #Bayesian #BayesFactor #guide #tutorial
link.springer.com/article/10.3...
Thoughts: @jaspstats.bsky.social is often people's first attempt at Bayesian statistics. But proper inference and reporting is crucial
#JASP #Bayesian #BayesFactor #guide #tutorial
link.springer.com/article/10.3...
The JASP guidelines for conducting and reporting a Bayesian analysis - Psychonomic Bulletin & Review
Despite the increasing popularity of Bayesian inference in empirical research, few practical guidelines provide detailed recommendations for how to apply Bayesian procedures and interpret the results....
link.springer.com
July 8, 2025 at 7:51 PM
#statstab #382 The JASP Guidelines for Conducting and Reporting a Bayesian Analysis
Thoughts: @jaspstats.bsky.social is often people's first attempt at Bayesian statistics. But proper inference and reporting is crucial
#JASP #Bayesian #BayesFactor #guide #tutorial
link.springer.com/article/10.3...
Thoughts: @jaspstats.bsky.social is often people's first attempt at Bayesian statistics. But proper inference and reporting is crucial
#JASP #Bayesian #BayesFactor #guide #tutorial
link.springer.com/article/10.3...
Nice! I did not know your book covered this.
My intuition about this was quite vague, based on the existence of p-value to BayesFactor calibrators with some sort of exponential limiting case. So I will study this!
My intuition about this was quite vague, based on the existence of p-value to BayesFactor calibrators with some sort of exponential limiting case. So I will study this!
August 7, 2026 at 10:48 AM
Nice! I did not know your book covered this.
My intuition about this was quite vague, based on the existence of p-value to BayesFactor calibrators with some sort of exponential limiting case. So I will study this!
My intuition about this was quite vague, based on the existence of p-value to BayesFactor calibrators with some sort of exponential limiting case. So I will study this!
Authors published a paper in Biorxiv, they used BayesFactor in the study. Including #RRIDs will make this less ambiguous.
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #reproducibility #OpenScience
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #reproducibility #OpenScience
www.biorxiv.org
August 6, 2026 at 12:00 PM
Authors published a paper in Biorxiv, they used BayesFactor in the study. Including #RRIDs will make this less ambiguous.
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #reproducibility #OpenScience
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #reproducibility #OpenScience
CRAN updates: BayesFactor breathtestcore fastcpd ggdag kisopenapi LEGIT MazamaLocationUtils MHD RApiDatetime TDA #rstats
January 24, 2024 at 4:02 PM
CRAN updates: BayesFactor breathtestcore fastcpd ggdag kisopenapi LEGIT MazamaLocationUtils MHD RApiDatetime TDA #rstats
Updates on CRAN: BayesFactor (0.9.12-4.8), bfp (0.0-50), contentanalysis (1.0.0), hypertext (1.1.0), lrstat (0.3.0), openxlsx2 (1.25), thisplot (0.3.6), Upsilon (0.1.1), wnl (0.8.5)
March 7, 2026 at 5:21 PM
Updates on CRAN: BayesFactor (0.9.12-4.8), bfp (0.0-50), contentanalysis (1.0.0), hypertext (1.1.0), lrstat (0.3.0), openxlsx2 (1.25), thisplot (0.3.6), Upsilon (0.1.1), wnl (0.8.5)
Updates on CRAN: arf (0.2.0), bartcs (1.2.1), BayesFactor (0.9.12-4.7), bcmaps (2.2.0), breathtestcore (0.8.7), causalweight (1.1.0), convdistr (1.6.1), CSIndicators (1.1.1), familiar (1.4.6), fastcpd (0.10.3), ggdag (0.2.11), GGIRread (0.3.3), kableExtra (1.4.0), kisopenapi (0.0.2), LEGIT (1.4.1)
January 24, 2024 at 5:17 PM
Updates on CRAN: arf (0.2.0), bartcs (1.2.1), BayesFactor (0.9.12-4.7), bcmaps (2.2.0), breathtestcore (0.8.7), causalweight (1.1.0), convdistr (1.6.1), CSIndicators (1.1.1), familiar (1.4.6), fastcpd (0.10.3), ggdag (0.2.11), GGIRread (0.3.3), kableExtra (1.4.0), kisopenapi (0.0.2), LEGIT (1.4.1)
#statstab #532 Fractional Bayes Factors for Model Comparison Free - O'Hagan (1995)
Thoughts: Use a fraction of the data to convert an improper prior into a minimally informative prior.
#bayesian #bayesfactor #priors #bain #hypothesis #testing
doi.org/10.1111/j.25...
Thoughts: Use a fraction of the data to convert an improper prior into a minimally informative prior.
#bayesian #bayesfactor #priors #bain #hypothesis #testing
doi.org/10.1111/j.25...
Fractional Bayes Factors for Model Comparison
SUMMARY. Bayesian comparison of models is achieved simply by calculation of posterior probabilities of the models themselves. However, there are difficulti
doi.org
May 14, 2026 at 5:41 PM
#statstab #532 Fractional Bayes Factors for Model Comparison Free - O'Hagan (1995)
Thoughts: Use a fraction of the data to convert an improper prior into a minimally informative prior.
#bayesian #bayesfactor #priors #bain #hypothesis #testing
doi.org/10.1111/j.25...
Thoughts: Use a fraction of the data to convert an improper prior into a minimally informative prior.
#bayesian #bayesfactor #priors #bain #hypothesis #testing
doi.org/10.1111/j.25...